Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BB6208BDB22835E48E0303CAB97223BFF14791BDEA5256D8E75482187294DFD8834EC5 |
|
CONTENT
ssdeep
|
192:QoAoB6CJ54t94lvKD4+v/W31tRahFhtku9cuGRmKbMpBXp7sfgg8gk:QVoCmvKvv/W3r4dysmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ef6b91b2d4803d94 |
|
VISUAL
aHash
|
ff8181b18181ffff |
|
VISUAL
dHash
|
617373476763799e |
|
VISUAL
wHash
|
ff8181818181ffee |
|
VISUAL
colorHash
|
07033000000 |
|
VISUAL
cropResistant
|
617373476763799e,40d4c29aabe2d2c0,2e363c6c5878340c,fffffe6d6afdefea |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 485 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.